Well placement planning is used in a number of industries to plan out the placement of prospective wells. In the oil & gas industry, for example, well placement planning is used to select placements and trajectories for proposed wells into a subsurface reservoir to reach specific locations in the reservoir that are believed to contain recoverable hydrocarbons.
Determining a suitable placement and trajectory for a well, however, is often complicated by the presence of subsurface hazards. The hazards may be in the form of existing wells and/or geological hazards such as salt bodies, faults and fracture networks. Particularly in some mature and/or large reservoirs, the hazard landscape can be extremely complex, as some reservoirs may have hundreds of existing wells, as well as geological hazards that need to be avoided when drilling a new well. In addition, as these hazards are within a subsurface, and potentially thousands of meters below the surface, the hazards necessarily have some degree of positional and geometric uncertainty, which further complicates the determination of a suitable placement and trajectory for a new well.
Conventionally, hazard avoidance analysis is performed within a three-dimensional environment, and is centered around the proposed trajectory of a well. At various points (also referred to as depths) along the proposed trajectory, a separation vector is defined from a point on the proposed trajectory to the closest point on a hazard (e.g., an existing well), and a risk of collision is calculated as a function of the uncertainty in both the proposed and existing wells (as a proposed well, as with an existing well, will also be subject to some degree of uncertainty). Performing hazard avoidance analysis in this manner, however, has been found to be extremely computationally expensive, in part due to the fact that the calculations are performed within a three dimensional environment, and are therefore mathematically complex.
In addition, it has been found that uncertainties in trajectory geometries are generally not isotropic. To better model such uncertainties, the uncertainty at a particular point on a well trajectory may be represented as a relatively complex geometric shape such as an ellipsoid normal to the well trajectory at that point, with the three principal axes of the ellipsoid representing measured depth uncertainty, azimuthal uncertainty, and inclination uncertainty. These respective uncertainty ellipsoids of a proposed and existing well may then be compared, honoring the potentially different orientations of the ellipsoids, with the value of the resulting oriented separation factor determining whether the proposed trajectory location is valid from a hazard-avoidance collision perspective. Such a computation, however, is generally repeated for every existing well or other hazard with respect to the proposed well. Further, the computations performed at one point along the trajectory of the proposed well also are repeated for other points along the trajectory.
While the latter approach has been found to be both precise and effective in many situations, the computations involved with the approach can be extremely expensive from a computational standpoint, particularly when the number of existing wells is very large, the geometry of the existing wells is complex, and/or the number of proposed wells being considered is large. In addition, in other workflows, such as well placement optimization, where an optimization engine proposes trajectory locations and geometries for multiple wells, and multiple trials are run to test new candidate trajectories, the computational expense of hazard avoidance can be prohibitive.
A need therefore exists in the art for a computationally efficient approach to hazard avoidance analysis.